Starfysh integration of all ccRCC samples¶

This vignette provides the code using Starfysh spot deconvolution on given signatures through integrative spatial deconvolution from multiple samples. The datasets here include 19 distinct TLS postivie ccRCC tumor samples from which 9 are responders to ICI treatment and 10 are non-responders.

In [2]:
#Import needed modules
import os
import numpy as np
import pandas as pd
import torch
import matplotlib.pyplot as plt
import matplotlib.font_manager
from matplotlib import rcParams

import seaborn as sns
sns.set_style('white')

font_list = []
fpaths = matplotlib.font_manager.findSystemFonts()
for i in fpaths:
    try:
        f = matplotlib.font_manager.get_font(i)
        font_list.append(f.family_name)
    except RuntimeError:
        pass

font_list = set(font_list)
plot_font = 'Helvetica' if 'Helvetica' in font_list else 'FreeSans'

rcParams['font.family'] = plot_font
rcParams.update({'font.size': 10})
rcParams.update({'figure.dpi': 300})
rcParams.update({'figure.figsize': (3,3)})
rcParams.update({'savefig.dpi': 500})

import warnings
warnings.filterwarnings('ignore')
In [3]:
#Load starfysh
from starfysh import (AA, utils, plot_utils, post_analysis)
from starfysh import starfysh as sf_model

Create sample meta info

In [ ]:
meta_info = [['P_1','P_1','processed_data/P_1/'],#Already downloaded, #First one is the name of the folder containing the data
             ['P_2','P_2','processed_data/P_2/'], #
             ['P_3','P_3','processed_data/P_3/'],#Already downloaded
             ['P_4','P_4','processed_data/P_4/'],#Already downloaded
             ['P_5','P_5','processed_data/P_5/'],#Already downloaded
             ['P_6','P_6','processed_data/P_6/'],#Already downloaded
             ['P_7','P_7','processed_data/P_7/'],#Already downloaded
             ['P_8','P_8','processed_data/P_8/'], #Already downloaded
             ['P_9','P_9','processed_data/P_9/'], #
            ['P_10','P_10','processed_data/P_10/'],#Already downloaded, #First one is the name of the folder containing the data
             ['P_11','P_11','processed_data/P_11/'], #
             ['P_12','P_12','processed_data/P_12/'],#Already downloaded
             ['P_13','P_13','processed_data/P_13/'],#Already downloaded
             ['P_14','P_14','processed_data/P_14/'],#Already downloaded
             ['P_15','P_15','processed_data/P_15/'],#Already downloaded
             ['P_16','P_16','processed_data/P_16/'],#Already downloaded
             ['P_17','P_17','processed_data/P_17/'], #Already downloaded
             ['P_18','P_18','processed_data/P_18/'],
             ['P_19','P_19','processed_data/P_19/'],
            ]
#CID44971_TNBC
meta_info = pd.DataFrame(meta_info,columns=['sample','anonymized_id','visiumPath'])
# Specify data paths
data_path = 'processed_data/' # root data directory
output_path = 'Starfysh_results/'
sample_id2 = 'outs' #name of the folder containing the data
#data_path = '../ToyData/'
#output_path = '../ToyData/Results_integrated/'
sig_file_name = 'Starfysh_results/Signatures_Starfysh.csv' #This is the Supplementary Table S13
print(meta_info)
for sample_id in meta_info['sample']:
    print(sample_id)
    data_path2 = meta_info['visiumPath'][list(meta_info['sample']).index(sample_id)]
    print(data_path2)
In [ ]:
adata_all = []
adata_normed_all = []
img_metadata_all = {}
for sample_id in meta_info['sample']:
    print(sample_id)
    data_path2 = meta_info['visiumPath'][list(meta_info['sample']).index(sample_id)]
    adata, adata_normed = utils.load_adata(data_folder=data_path2,  # root data directory
                                       sample_id=sample_id2,  # sample_id
                                       n_genes=2000  # number of highly variable genes to keep
                                      )
    
    
    adata_all.append(adata)
    adata_normed_all.append(adata_normed)
    
    img_metadata = utils.preprocess_img(data_path2,
                                    sample_id2,
                                    adata_index=adata.obs.index,
                                    hchannel=True #Must be true otherwise POE wont work
                                    )
    #From: https://github.com/azizilab/starfysh/issues/31
    
    adata.obs['anonymized_id']=meta_info['anonymized_id'][list(meta_info['sample']).index(sample_id)]
    #adata.obs['RECIST_R_nR']=meta_info['RECIST_R_nR'][list(meta_info['sample']).index(sample_id)] #Clinical data can be
    #demanded to authors
    adata.obs['patient']=meta_info['sample'][list(meta_info['sample']).index(sample_id)]
    adata.obs['sample']=meta_info['sample'][list(meta_info['sample']).index(sample_id)]
    #sample_id_3 = meta_info['anonymized_id'][list(meta_info['sample']).index(sample_id)]
    adata.obs_names  = adata.obs_names+'-'+sample_id

    adata_normed.obs['anonymized_id']=adata.obs['anonymized_id']
    adata_normed.obs['patient']=adata.obs['patient']
    #adata_normed.obs['RECIST_R_nR']=adata.obs['RECIST_R_nR'] #Clinical data can be
    #demanded to authors

    img_metadata['map_info'].index = img_metadata['map_info'].index+'-'+sample_id
    img_metadata_all[sample_id] = img_metadata 
In [16]:
# Save concat data
import anndata
import scanpy as sc
adata_all = anndata.concat(adata_all)
adata_normed_all = anndata.concat(adata_normed_all)
sc.pp.highly_variable_genes(adata_normed_all)
adata_all.uns = adata_normed_all.uns
adata_all.var = adata_normed_all.var
In [17]:
#Check
print(adata_all)
print(adata_normed_all)
AnnData object with n_obs × n_vars = 75259 × 13200
    obs: 'in_tissue', 'array_row', 'array_col', 'sample', 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_50_genes', 'pct_counts_in_top_100_genes', 'pct_counts_in_top_200_genes', 'pct_counts_in_top_500_genes', 'total_counts_mt', 'log1p_total_counts_mt', 'pct_counts_mt', 'anonymized_id', 'RECIST_R_nR', 'patient'
    var: 'highly_variable', 'means', 'dispersions', 'dispersions_norm'
    uns: 'hvg'
    obsm: 'spatial'
AnnData object with n_obs × n_vars = 75259 × 13200
    obs: 'in_tissue', 'array_row', 'array_col', 'sample', 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_50_genes', 'pct_counts_in_top_100_genes', 'pct_counts_in_top_200_genes', 'pct_counts_in_top_500_genes', 'total_counts_mt', 'log1p_total_counts_mt', 'pct_counts_mt', 'anonymized_id', 'RECIST_R_nR', 'patient'
    var: 'highly_variable', 'means', 'dispersions', 'dispersions_norm'
    uns: 'hvg'
    obsm: 'spatial'
In [8]:
# Load signatures
gene_sig = pd.read_csv(os.path.join(sig_file_name))
gene_sig = utils.filter_gene_sig(gene_sig, adata_all.to_df())
gene_sig.head()
Out[8]:
Tcm Tem Tfh Treg Activated CD8 Dysfunc CD8 Terminal exhaustion Precursor exhaustion NK B cells memory ... Monocytes cDC pDC CAFs MSC iCAF-like CAFs myCAF-like Endothelial PT_like ProInflammatory EMT_like PI3K
0 CCR7 IL7R CXCL13 TNFRSF4 CD69 NPEPPS CD3G TCF7 GNLY MS4A1 ... LYZ CD80 IL3RA APOD COL1A1 ACKR1 TRPM3 AL078604.4 EEF1G ERBB4
1 LTB ANXA1 NMB LTB CCR7 NOTCH2 FASLG MS4A4A XCL1 CD79A ... IL1B CD86 LILRA4 DCN COL1A2 FABP4 PBX1 BIRC3 FAU GRHL2
2 IL7R CXCR4 NR3C1 IL32 CD27 CABLES1 ID2 TNFSF8 XCL2 CD83 ... G0S2 CCR7 CD123 PTGDS COL3A1 PLVAP SLC6A13 DCLK1 UBA52 SIM2
3 SARAF KLRB1 DUSP4 BATF BTLA CERK LAG3 CXCL10 AREG CD37 ... TYROBP CD1A TCF4 CFD LUM RAMP2 SLC17A4 PDE10A MIF SCHLAP1
4 SELL TNFAIP3 TNFRSF18 FOXP3 CD40LG MTMR3 RGS1 EEF1B2 KLRD1 BANK1 ... FCN1 CD1C IRF7 LUM SFRP2 VWF SLC6A12 FKBP5 EEF2 ESRP1

5 rows × 25 columns

In [19]:
#Save data
# Save concat data
import anndata
import scanpy as sc
#adata_all.write(os.path.join(output_path, 'adata_all.h5ad'))
#adata_normed_all.write(os.path.join(output_path, 'adata_normed_all.h5ad'))
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
... storing 'patient' as categorical
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
... storing 'patient' as categorical
In [6]:
#Load if needed
# Save concat data
import anndata
import scanpy as sc
adata_all = sc.read_h5ad(os.path.join(output_path, 'adata_all.h5ad'))
adata_normed_all = sc.read_h5ad(os.path.join(output_path, 'adata_normed_all.h5ad'))

Preprocessing: Run archetypes separately to update gene signature¶

In [9]:
from starfysh.AA import ArchetypalAnalysis
def assign_archetypes(anchor_df, r=30):
    """
    Assign best 1-1 mapping of archetype community to its closest anchor community (cell-type specific anchor spots)
    Criteria: choose the top cell type in which its anchors belongs to the top r neighbors to the given archetype

    Parameters
    ----------
    anchor_df : pd.DataFrame
        Dataframe of anchor spot indices

`       r : int
        Resolution parameter to threshold archetype - anchor mapping

    Returns
    -------
    map_df : pd.DataFrame
        DataFrame of overlapping spot ratio of each anchor `i` to archetype `j`

    map_dict : dict
        Dictionary of cell type -> mapped archetype
    """
    assert aa_model.arche_df is not None, "Please compute archetypes & assign nearest-neighbors first!"

    n_nbrs, n_archetypes = aa_model.arche_df.shape # number of archetypal spots for each archtype, number of archetypes
    x_concat = np.vstack([aa_model.count, aa_model.archetype])
    anchor_nbrs = anchor_df.values
    archetypal_nbrs = aa_model._get_knns(x_concat, n_nbrs=r, indices=aa_model.n_spots+aa_model.major_idx).T  # r-nearest nbrs to each archetype

    
    
    print(archetypal_nbrs.shape)
    overlaps = np.array(
        [
            [
                len(np.intersect1d(anchor_nbrs[:, i], archetypal_nbrs[:, j]))
                for j in range(archetypal_nbrs.shape[1])
            ]
            for i in range(anchor_nbrs.shape[1])
        ]
    )
    overlaps_df = pd.DataFrame(overlaps, index=anchor_df.columns, columns=aa_model.arche_df.columns)
    arche_argmaxs = overlaps.argmax(0)
    
    distance_df = pd.DataFrame(np.zeros([anchor_df.shape[1],
                                         aa_model.arche_df.shape[1]]), 
                               index=anchor_df.columns, 
                               columns=aa_model.arche_df.columns
                              )
    for i in range(distance_df.shape[0]):
        for j in range(distance_df.shape[1]):
            dist_tmp = 0
            for kk in anchor_df.iloc[:,i]:
                dist_tmp += np.linalg.norm(aa_model.count[kk,:] - 
                                           aa_model.archetype[j,:]
                                          )
            
            distance_df.iloc[i,j] = dist_tmp
    
    map_dict = {}
    for k in range(overlaps.shape[0]):
        list_ = np.argsort(overlaps[k])[::-1]
        for i in list_:
            if (np.argsort(overlaps[:,i])[::-1][0]==k):
                if ((overlaps[k,:]==overlaps[k,i]).sum()==1):
                    map_dict[anchor_df.columns[k]]=aa_model.arche_df.columns[i]
                break 
                
                
    map_dict2 = {}
    for k in range(distance_df.shape[0]):
        list_ = np.argsort(np.array(distance_df)[k])
        #print(list_)
        for i in list_:
            if (np.argsort(np.array(distance_df)[:,i])[0]==k):
                if ((np.array(distance_df)[k,:]==np.array(distance_df)[k,i]).sum()==1):
                    map_dict2[anchor_df.columns[k]]=aa_model.arche_df.columns[i]
                break 
                
    return overlaps_df, distance_df,map_dict,map_dict2
In [10]:
import importlib
importlib.reload(utils)

gene_sig_all = []
visium_args_all = {}
for sample_id in meta_info['anonymized_id']:
    print(sample_id)
    adata = adata_all[adata_all.obs['anonymized_id']==sample_id]
    adata_normed = adata_normed_all[adata_normed_all.obs['anonymized_id']==sample_id]
    
    sc.pp.highly_variable_genes(adata_normed)
    adata.uns = adata_normed.uns
    adata.var = adata_normed.var

    img_metadata = img_metadata_all[sample_id]
    
    visium_args = utils.VisiumArguments(adata,
                                    adata_normed,
                                    gene_sig,
                                    img_metadata,
                                    window_size=4,
                                    sample_id=sample_id2,#'outs'
                                    n_img_chan = 1,
                                   )
    adata, adata_normed = visium_args.get_adata()
    anchors_df = visium_args.get_anchors()
    aa_model = AA.ArchetypalAnalysis(adata_orig=adata,
                                      # n_neighbors=100  #Atgument not detected
                                    )
    archetype, arche_dict, major_idx, evs = aa_model.compute_archetypes(cn=100, 
                                                                    #r=5,  not used
                                                                    converge=1e-3,
                                                                    display=False)

    arche_df = aa_model.find_archetypal_spots()
    
    markers_df = aa_model.find_markers(n_markers=30, display=False)
    
    percent_anchor = 0.01
    map_df, distance_df,map_dict,map_dict2 = assign_archetypes(anchors_df[:int(percent_anchor*adata.shape[0])], 
                                     r=int(percent_anchor*adata.shape[0])
                                    )  # here we subset the `r` top archetypes
    gene_sig_arch = gene_sig.copy()

    for cell_type in map_dict.keys():
        arch = map_dict[cell_type]
        gene_sig_arch = utils.append_sigs(gene_sig_arch, cell_type, markers_df[arch], n_genes=10)
    gene_sig_all.append(gene_sig_arch)
    visium_args_all[sample_id] = visium_args
P_1
[2024-04-29 11:05:47] Subsetting highly variable & signature genes ...
[2024-04-29 11:05:55] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:05:55] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:05:57] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:06:00] Computing intrinsic dimension to estimate k...
23 components are retained using conditional_number=100.00
[2024-04-29 11:06:01] Estimating lower bound of # archetype as 8...
[2024-04-29 11:07:14] 0.8892 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 11:07:14] Finding 100 nearest neighbors for each archetype...
[2024-04-29 11:07:14] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(13, 14)
P_2
[2024-04-29 11:07:19] Subsetting highly variable & signature genes ...
[2024-04-29 11:08:06] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:08:09] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:08:14] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:08:47] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 11:08:48] Estimating lower bound of # archetype as 11...
[2024-04-29 11:11:13] 0.8618 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 11:11:13] Finding 100 nearest neighbors for each archetype...
[2024-04-29 11:11:13] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(47, 16)
P_3
[2024-04-29 11:11:27] Subsetting highly variable & signature genes ...
[2024-04-29 11:11:59] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:12:00] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:12:04] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:12:27] Computing intrinsic dimension to estimate k...
27 components are retained using conditional_number=100.00
[2024-04-29 11:12:28] Estimating lower bound of # archetype as 12...
[2024-04-29 11:14:35] 0.8875 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 11:14:35] Finding 100 nearest neighbors for each archetype...
[2024-04-29 11:14:35] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(38, 16)
P_4
[2024-04-29 11:14:48] Subsetting highly variable & signature genes ...
[2024-04-29 11:14:56] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:14:57] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:14:59] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:15:06] Computing intrinsic dimension to estimate k...
[2024-04-29 11:15:06] Estimating lower bound of # archetype as 12...
30 components are retained using conditional_number=100.00
[2024-04-29 11:17:58] 0.8667 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 11:17:58] Finding 100 nearest neighbors for each archetype...
[2024-04-29 11:17:58] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(20, 18)
P_5
[2024-04-29 11:18:05] Subsetting highly variable & signature genes ...
[2024-04-29 11:18:58] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:19:00] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:19:05] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:19:42] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 11:19:43] Estimating lower bound of # archetype as 11...
[2024-04-29 11:26:03] 0.8954 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 11:26:03] Finding 100 nearest neighbors for each archetype...
[2024-04-29 11:26:03] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(49, 20)
P_6
[2024-04-29 11:26:30] Subsetting highly variable & signature genes ...
[2024-04-29 11:26:58] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:27:01] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:27:06] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:27:42] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 11:27:43] Estimating lower bound of # archetype as 12...
[2024-04-29 11:42:19] 0.7654 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 11:42:19] Finding 100 nearest neighbors for each archetype...
[2024-04-29 11:42:20] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(49, 20)
P_7
[2024-04-29 11:43:06] Subsetting highly variable & signature genes ...
[2024-04-29 11:44:37] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:44:38] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:44:41] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:44:52] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 11:44:52] Estimating lower bound of # archetype as 16...
[2024-04-29 11:48:29] 0.7851 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 11:48:29] Finding 100 nearest neighbors for each archetype...
[2024-04-29 11:48:29] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(25, 20)
P_8
[2024-04-29 11:48:38] Subsetting highly variable & signature genes ...
[2024-04-29 11:48:59] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:49:00] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:49:03] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:49:19] Computing intrinsic dimension to estimate k...
29 components are retained using conditional_number=100.00
[2024-04-29 11:49:20] Estimating lower bound of # archetype as 10...
[2024-04-29 11:52:33] 0.8909 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 11:52:33] Finding 100 nearest neighbors for each archetype...
[2024-04-29 11:52:33] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(32, 16)
P_9
[2024-04-29 11:52:43] Subsetting highly variable & signature genes ...
[2024-04-29 11:52:50] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:52:50] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:52:52] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:52:54] Computing intrinsic dimension to estimate k...
[2024-04-29 11:52:55] Estimating lower bound of # archetype as 12...
30 components are retained using conditional_number=100.00
[2024-04-29 11:54:00] 0.8711 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 11:54:00] Finding 100 nearest neighbors for each archetype...
[2024-04-29 11:54:00] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(10, 13)
P_10
[2024-04-29 11:54:04] Subsetting highly variable & signature genes ...
[2024-04-29 11:54:33] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 11:54:35] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 11:54:40] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 11:55:14] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 11:55:15] Estimating lower bound of # archetype as 8...
[2024-04-29 12:00:41] 0.9363 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:00:41] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:00:41] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(47, 21)
P_11
[2024-04-29 12:01:05] Subsetting highly variable & signature genes ...
[2024-04-29 12:02:07] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 12:02:09] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 12:02:14] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 12:02:52] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 12:02:52] Estimating lower bound of # archetype as 11...
[2024-04-29 12:09:08] 0.9184 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:09:08] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:09:09] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(49, 27)
P_12
[2024-04-29 12:09:39] Subsetting highly variable & signature genes ...
[2024-04-29 12:10:08] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 12:10:10] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 12:10:15] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 12:10:48] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 12:10:49] Estimating lower bound of # archetype as 13...
[2024-04-29 12:11:49] 0.8439 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:11:49] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:11:49] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(47, 14)
P_13
[2024-04-29 12:11:58] Subsetting highly variable & signature genes ...
[2024-04-29 12:12:27] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 12:12:29] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 12:12:34] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 12:13:05] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 12:13:06] Estimating lower bound of # archetype as 8...
[2024-04-29 12:18:12] 0.9134 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:18:12] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:18:13] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(45, 26)
P_14
[2024-04-29 12:18:29] Subsetting highly variable & signature genes ...
[2024-04-29 12:18:51] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 12:18:53] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 12:18:57] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 12:19:17] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 12:19:17] Estimating lower bound of # archetype as 7...
[2024-04-29 12:23:24] 0.9085 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:23:24] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:23:24] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(35, 23)
P_15
[2024-04-29 12:23:44] Subsetting highly variable & signature genes ...
[2024-04-29 12:24:28] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 12:24:30] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 12:24:35] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 12:25:12] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 12:25:13] Estimating lower bound of # archetype as 8...
[2024-04-29 12:30:53] 0.8859 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:30:53] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:30:54] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(49, 25)
P_16
[2024-04-29 12:31:27] Subsetting highly variable & signature genes ...
[2024-04-29 12:31:45] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 12:31:47] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 12:31:52] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 12:32:24] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 12:32:24] Estimating lower bound of # archetype as 7...
[2024-04-29 12:37:15] 0.84 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:37:15] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:37:16] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(46, 25)
P_17
[2024-04-29 12:37:35] Subsetting highly variable & signature genes ...
[2024-04-29 12:38:03] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 12:38:05] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 12:38:10] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 12:38:47] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 12:38:48] Estimating lower bound of # archetype as 11...
[2024-04-29 12:44:57] 0.9504 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:44:58] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:44:58] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(49, 24)
P_18
[2024-04-29 12:45:26] Subsetting highly variable & signature genes ...
[2024-04-29 12:45:58] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 12:46:00] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 12:46:05] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 12:46:33] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 12:46:34] Estimating lower bound of # archetype as 10...
[2024-04-29 12:52:06] 0.9056 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:52:06] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:52:06] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(43, 21)
P_19
[2024-04-29 12:52:23] Subsetting highly variable & signature genes ...
[2024-04-29 12:52:57] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 12:52:59] Retrieving & normalizing signature gene expressions...
WARNING: genes are not in var_names and ignored: ['SARAF', 'BTG1']
WARNING: genes are not in var_names and ignored: ['FYB', 'IL21']
WARNING: genes are not in var_names and ignored: ['AC133644.2', 'CACYBP', 'LAIR2', 'BTG1']
WARNING: genes are not in var_names and ignored: ['IFNG', 'CD95L']
WARNING: genes are not in var_names and ignored: ['KLF3', 'MIR466I', 'TUBB2B', 'MNDAL', 'TMEM55B', 'FAM196B']
WARNING: genes are not in var_names and ignored: ['CCL3 CCL3L1', 'CD160', 'PLAC8', 'ARL6IP1']
WARNING: genes are not in var_names and ignored: ['XCL2', 'KRT86']
WARNING: genes are not in var_names and ignored: ['CD83', 'HLA-DQB1', 'HLA-DQA2', 'LINC00926', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['TCL1A', 'LINC00926', 'HLA-DQB1', 'FCER2', 'CD83', 'BACH2', 'BTG1', 'FAM129C', 'HLA-DQA2', 'HLA-DRB5']
WARNING: genes are not in var_names and ignored: ['CCL3', 'CCL3L3', 'SEPP1', 'HLA-DRB1', 'GPX1', 'HLA-DRB5', 'HLA-DQB1', 'CD83', 'CCL4L2']
WARNING: genes are not in var_names and ignored: ['FAM26F', 'HLA-DRB5', 'HLA-DRB1', 'CCL3', 'HLA-DQB1', 'CCL3L3', 'GPX1']
WARNING: genes are not in var_names and ignored: ['IGKV3-15', 'IGKV1-5', 'IGKV3-20', 'IGKV3-11', 'IGKV1-9', 'IGLV2-14', 'IGLV3-25', 'IGLV1-40', 'IGLV1-44', 'IGHV6-1', 'IGLC2', 'IGLV1-51', 'IGHV3-23', 'IGHV3-21', 'IGLV3-21', 'IGLC3', 'IGLV1-47', 'IGHV3-30', 'IGLV3-1', 'IGLV2-23', 'IGLV2-11', 'IGHV4-39', 'IGHV1-18', 'IGHV1-46', 'CH17-224D4.2', 'IGLV2-8', 'IGKV1-8', 'IGLV4-69', 'IGKV1-16', 'IGKV3D-11', 'IGHV3-15', 'IGHV3-74', 'IGLV3-19']
WARNING: genes are not in var_names and ignored: ['ARG1']
WARNING: genes are not in var_names and ignored: ['GPX1', 'HLA-DRB1', 'HLA-DRB5', 'HLA-DQB1', 'FAM26F', 'RP11-1143G9.4', 'CCL3', 'CCL3L3', 'CD83']
WARNING: genes are not in var_names and ignored: ['CD1A', 'CD1C', 'CD11b', 'CD11C', 'CD16', 'CD83', 'CD123', 'CD141', 'EpCAM', 'HLA-DR', 'CD207', 'CD172A']
WARNING: genes are not in var_names and ignored: ['CD123', 'IFNA', 'IFNB', 'TNFA']
WARNING: genes are not in var_names and ignored: ['IGF2', 'CYR61', 'CTGF', 'MEG3']
WARNING: genes are not in var_names and ignored: ['CTGF']
WARNING: genes are not in var_names and ignored: ['SDPR', 'PDLIM1', 'PTRF', 'FLT1', 'CXorf36']
WARNING: genes are not in var_names and ignored: ['TRPM3', 'SLC17A4', 'CCSER1', 'SLC6A3', 'AC124854.1', 'ACSM2B', 'SLC5A8', 'FTCD', 'SLC27A2', 'PCK1', 'CDHR2', 'ACE2', 'HAVCR1', 'ZMAT4', 'ACMSD', 'UGT2A3']
WARNING: genes are not in var_names and ignored: ['AL078604.4', 'AP002518.2', 'MIR31HG']
WARNING: genes are not in var_names and ignored: ['FAU', 'TMSB10', 'GAPDH', 'TPT1', 'TUBB']
WARNING: genes are not in var_names and ignored: ['ERBB4', 'GRHL2', 'SIM2', 'SCHLAP1', 'ESRP1', 'TMPRSS4', 'GABRP', 'ADGRF1', 'SLC12A1', 'LYPD6B', 'ARHGEF38', 'LRP1B', 'PRDM16', 'PWRN1', 'HS6ST3']
[2024-04-29 12:53:05] Identifying anchor spots (highly expression of specific cell-type signatures)...
[2024-04-29 12:53:41] Computing intrinsic dimension to estimate k...
30 components are retained using conditional_number=100.00
[2024-04-29 12:53:42] Estimating lower bound of # archetype as 10...
[2024-04-29 12:59:37] 0.934 variance explained by raw archetypes.
Merging raw archetypes within 100 NNs to get major archetypes
[2024-04-29 12:59:37] Finding 100 nearest neighbors for each archetype...
[2024-04-29 12:59:38] Finding 30 top marker genes for each archetype...
... storing 'sample' as categorical
... storing 'anonymized_id' as categorical
... storing 'RECIST_R_nR' as categorical
(49, 23)
In [13]:
gene_sig
Out[13]:
Tcm Tem Tfh Treg Activated CD8 Dysfunc CD8 Terminal exhaustion Precursor exhaustion NK B cells memory ... Monocytes cDC pDC CAFs MSC iCAF-like CAFs myCAF-like Endothelial PT_like ProInflammatory EMT_like PI3K
0 CCR7 IL7R CXCL13 TNFRSF4 CD69 NPEPPS CD3G TCF7 GNLY MS4A1 ... LYZ CD80 IL3RA APOD COL1A1 ACKR1 TRPM3 AL078604.4 EEF1G ERBB4
1 LTB ANXA1 NMB LTB CCR7 NOTCH2 FASLG MS4A4A XCL1 CD79A ... IL1B CD86 LILRA4 DCN COL1A2 FABP4 PBX1 BIRC3 FAU GRHL2
2 IL7R CXCR4 NR3C1 IL32 CD27 CABLES1 ID2 TNFSF8 XCL2 CD83 ... G0S2 CCR7 CD123 PTGDS COL3A1 PLVAP SLC6A13 DCLK1 UBA52 SIM2
3 SARAF KLRB1 DUSP4 BATF BTLA CERK LAG3 CXCL10 AREG CD37 ... TYROBP CD1A TCF4 CFD LUM RAMP2 SLC17A4 PDE10A MIF SCHLAP1
4 SELL TNFAIP3 TNFRSF18 FOXP3 CD40LG MTMR3 RGS1 EEF1B2 KLRD1 BANK1 ... FCN1 CD1C IRF7 LUM SFRP2 VWF SLC6A12 FKBP5 EEF2 ESRP1
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
95 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
96 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
97 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
98 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
99 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN

100 rows × 25 columns

Preprocessing: integrate data¶

This step is for identifying the anchor spots and providing prior for model training.

utils.VisiumArguments is called for each sample (performed already when updating the signature using archetypes, stored as 'visium_args_all'), followed by utils_integrate.VisiumArguments_integrate for integrating all priors.

Starfysh calcualates cell-type proportion scores for each spot per sample given the annotated signatures (per cell type) as the model's prior

Each spot will be ranked (anchors_df) based on the prior, which represents the rough estimation of the given cell-type's enrichment

In [23]:
adata_normed_all
Out[23]:
AnnData object with n_obs × n_vars = 75259 × 13200
    obs: 'in_tissue', 'array_row', 'array_col', 'sample', 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_50_genes', 'pct_counts_in_top_100_genes', 'pct_counts_in_top_200_genes', 'pct_counts_in_top_500_genes', 'total_counts_mt', 'log1p_total_counts_mt', 'pct_counts_mt', 'anonymized_id', 'RECIST_R_nR', 'patient'
    var: 'highly_variable', 'means', 'dispersions', 'dispersions_norm'
    uns: 'hvg'
    obsm: 'spatial'
In [26]:
from starfysh import utils_integrate
importlib.reload(utils_integrate)

sc.pp.highly_variable_genes(adata_normed_all)
adata_all.uns = adata_normed_all.uns
adata_all.var = adata_normed_all.var


visium_args = utils_integrate.VisiumArguments_integrate(adata_all,
                                    adata_normed_all,
                                    gene_sig, ##Stay with normal signature
                                    img_metadata_all,
                                    visium_args_all,                                        
                                    window_size=3,
                                    sample_id=meta_info['sample']
                                   )
[2024-04-29 19:40:18] Subsetting highly variable & signature genes ...
[2024-04-29 19:40:21] Smoothing library size by taking averaging with neighbor spots...
[2024-04-29 19:40:58] Retrieving & normalizing signature gene expressions...
[2024-04-29 19:40:58] Identifying anchor spots (highly expression of specific cell-type signatures)...
In [27]:
import importlib
importlib.reload(sf_model)

from starfysh import utils_integrate
importlib.reload(utils_integrate)
Out[27]:
<module 'starfysh.utils_integrate' from '/home/isaias/.local/share/r-miniconda/envs/r-reticulate/lib/python3.8/site-packages/starfysh/utils_integrate.py'>

Processing: Run Starfysh for joint spatial deconvolution & sample integration¶

(1) Model parameters

In [28]:
n_repeats = 1
epochs = 100
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
In [29]:
import importlib
importlib.reload(utils_integrate)
Out[29]:
<module 'starfysh.utils_integrate' from '/home/isaias/.local/share/r-miniconda/envs/r-reticulate/lib/python3.8/site-packages/starfysh/utils_integrate.py'>
In [34]:
adata
Out[34]:
AnnData object with n_obs × n_vars = 4936 × 13200
    obs: 'in_tissue', 'array_row', 'array_col', 'sample', 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_50_genes', 'pct_counts_in_top_100_genes', 'pct_counts_in_top_200_genes', 'pct_counts_in_top_500_genes', 'total_counts_mt', 'log1p_total_counts_mt', 'pct_counts_mt', 'anonymized_id', 'RECIST_R_nR', 'patient'
    var: 'highly_variable', 'means', 'dispersions', 'dispersions_norm'
    uns: 'hvg', 'cell_types'
    obsm: 'spatial'

(2). Model training

In [35]:
model, loss = utils_integrate.run_starfysh(visium_args,
                                 n_repeats=n_repeats,
                                 epochs=epochs,
                                 poe=True, #Means histology to be used...
                                 device=device)
[2024-04-29 20:00:28] Running Starfysh with 1 restarts, choose the model with best parameters...
[2024-04-29 20:00:28]  ===  Restart Starfysh 1 === 

[2024-04-29 20:00:28] Initializing model parameters...
[2024-04-29 20:14:26] Epoch[10/100], train_loss: 7163.9827, train_reconst: 6954.7536, train_u: 13.5052,train_z: 36.2660,train_c: 95.8831,train_n: 63.5748
[2024-04-29 20:28:17] Epoch[20/100], train_loss: 6653.4592, train_reconst: 6451.1382, train_u: 12.1844,train_z: 41.8874,train_c: 83.4769,train_n: 64.7722
[2024-04-29 20:42:08] Epoch[30/100], train_loss: 6666.6284, train_reconst: 6469.7888, train_u: 11.8632,train_z: 41.5447,train_c: 78.2523,train_n: 65.1794
[2024-04-29 20:55:50] Epoch[40/100], train_loss: 6518.8326, train_reconst: 6326.1833, train_u: 11.8387,train_z: 40.8535,train_c: 74.3282,train_n: 65.6289
[2024-04-29 21:09:40] Epoch[50/100], train_loss: 6423.5089, train_reconst: 6233.7970, train_u: 11.9583,train_z: 40.5227,train_c: 71.1362,train_n: 66.0947
[2024-04-29 21:23:35] Epoch[60/100], train_loss: 6381.2035, train_reconst: 6193.9551, train_u: 12.1276,train_z: 40.1263,train_c: 68.3863,train_n: 66.6083
[2024-04-29 21:37:49] Epoch[70/100], train_loss: 6342.5779, train_reconst: 6157.7389, train_u: 12.2960,train_z: 39.6013,train_c: 66.2523,train_n: 66.6894
[2024-04-29 21:52:11] Epoch[80/100], train_loss: 6252.4254, train_reconst: 6069.1305, train_u: 12.4573,train_z: 39.4165,train_c: 64.4898,train_n: 66.9313
[2024-04-29 22:06:36] Epoch[90/100], train_loss: 6224.7530, train_reconst: 6043.2759, train_u: 12.5965,train_z: 38.7373,train_c: 63.0056,train_n: 67.1377
[2024-04-29 22:21:00] Epoch[100/100], train_loss: 6199.6327, train_reconst: 6019.8916, train_u: 12.7062,train_z: 38.0655,train_c: 61.8222,train_n: 67.1472
[2024-04-29 22:21:00] Saving the best-performance model...
[2024-04-29 22:21:00]  === Finished training === 

In [36]:
# Save model
torch.save(model.state_dict(), os.path.join(output_path, 'integ_model.pt'))
In [37]:
inference_outputs, generative_outputs = sf_model.model_eval_integrate(model,
                                                                      visium_args.adata,
                                                                      visium_args,
                                                                      poe=True,
                                                                      device=device
                                                                     )
rv: px_r_poe can't be stored
In [38]:
##Extract integrated object to a different object
adata_integrate = visium_args.adata.copy()
adata_integrate.shape
Out[38]:
(75259, 2738)
In [39]:
adata_inte_2 = adata_integrate.copy() #Copy just in case
In [40]:
#save integrated object
adata_inte_2.write(os.path.join(output_path,'adata_integrated.h5ad'))
In [ ]:
##
# Deconvolution prediction
prop_pred_df = pd.DataFrame(adata_integrate.obsm['qc_m'], index=adata_integrate.obs_names, columns=gene_sig.columns)
prop_pred_df
In [42]:
##Save deconvolution values
##Export results from deconvolution...
prop_pred_df.to_csv(os.path.join(output_path,'Starfysh_integrated_obs_all.csv'), index=True) ##This file is needed
#to reproduce Figure 3 and 4
In [43]:
###UMAP before sample integration
adata_all2 = adata_all[:, adata_integrate.var_names]
sc.pp.neighbors(adata_all2, use_rep='X', n_neighbors=20)
sc.tl.umap(adata_all2, min_dist=0.2)
In [44]:
#Plot
fig, ax = plt.subplots(1, 1, figsize=(10, 10), dpi=200)
ax = sc.pl.umap(adata_all2, color='anonymized_id', 
               frameon=False, s=25, ax=ax,
               title='UMAP without Starfysh sample integration'
              )
fig.savefig(os.path.join(output_path,'UMAP_notIntegrated.pdf'),transparent=True,dpi=1000)
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In [46]:
###UMAP after sample integration
###Add deconvolution values stored in 'obsm'['qc_m']
adata_integrate.obs[gene_sig.columns]=pd.DataFrame(adata_integrate.obsm['qc_m'],
                                                   columns=gene_sig.columns,
                                                   index=adata_integrate.obs_names)
sc.pp.neighbors(adata_integrate,use_rep='qc_m',n_neighbors=20)
sc.tl.umap(adata_integrate,  min_dist=0.2)
In [47]:
#Plot
fig, ax = plt.subplots(1, 1, figsize=(10,10), dpi=300)
ax = sc.pl.umap(adata_integrate,color='anonymized_id',
                frameon=False, s=5, ax=ax,
                title='UMAP after Starfysh sample integration'
                )
fig.savefig(os.path.join(output_path,'UMAP_Integrated.pdf'),transparent=True,dpi=1000)
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In [50]:
####UMAP plotting some pops of interest....
#For Treg
sc.settings.set_figure_params(dpi=300, facecolor='white')
sc.settings.set_figure_params(dpi=500, facecolor='white')
fig,ax = plt.subplots(1,1,figsize=(4,3.2),dpi=500)

sc.pl.umap(adata_integrate,color="Treg",frameon=False,
           vmax=0.2,
           s=10,
           cmap='Spectral_r',
           ax=ax,
           title=''
          )
fig.savefig(os.path.join(output_path,'UMAP_Integrated_Treg.pdf'),transparent=True,dpi=1000,bbox_inches='tight')
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